code: def plot(title=""):
      plt.figure(figsize=(12, 4))
      plt.title(title)
      pX = np.linspace(-1, 1, 100)[:, None]  # Test locations
      pY, pYv = m.predict_y(pX)  # Predict Y values at test locations
      plt.plot(X, Y, "x", label="Training points", alpha=0.2)
      (line,) = plt.plot(
          pX, pY, lw=1.5, label="Mean of predictive posterior"
      )
      col = line.get_color()
      plt.fill_between(
          pX[:, 0],
          (pY - 2 * pYv**0.5)[:, 0],
          (pY + 2 * pYv**0.5)[:, 0],
          color=col,
          alpha=0.6,
          lw=1.5,
      )
      Z = m.inducing_variable.Z.numpy()
      plt.plot(
          Z, np.zeros_like(Z), "k|", mew=2, label="Inducing locations"
      )
      plt.legend(loc="lower right")
  
file_path: GPflow/doc/sphinx/notebooks/advanced/gps_for_big_data.pct.py
imports: import itertools
  import time
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import gpflow
  from gpflow.ci_utils import reduce_in_tests
label_desc: Use image node_id 2 for calling a global function with example usage: plot(title) without return types